Biology subjects

Freddolino, L.

Publications and source records attributed to Freddolino, L..

4 recordsLinked to original sources

bioRxiv2024

Negative feedback of cyclic di-GMP levels optimizes switching between sessile and motile lifestyles in Vibrio cholerae

The signaling molecule cyclic di-GMP (c-di-GMP) controls the switch between bacterial motility and biofilm production, and fluctuations in cellular levels of c-di-GMP have been implicated in Vibrio cholerae pathogenesis. Intracellular concentrations of c-di-GMP are controlled by the interplay of diguanylate cyclase (DGC) enzymes, which synthesize c-di-GMP to promote biofilms, and phosphodiesterase (PDE) enzymes, which hydrolyze c-di-GMP to drive motility. To track the complete regulatory logic of how V. cholerae responds to changing c-di-GMP levels, we followed a time course of overexpression of either the V. campbellii diguanylate cyclase QrgB or a variant of QrgB lacking catalytic activity (QrgB*). We find that QrgB increases c-di-GMP levels relative to QrgB* for 30 minutes after overexpression, but the effect of QrgB on c-di-GMP levels plateaus at 30 minutes, indicating tight adaptive control of c-di-GMP levels. In contrast, loss of VpsR, a master regulator activating biofilm formation upon binding to c-di-GMP, leads to higher baseline levels of c-di-GMP and continuously increasing c-di-GMP through 60 minutes after QrgB induction, revealing the existence of a negative feedback loop on c-di-GMP levels operating through VpsR. Through a combination of RNA polymerase ChIP-seq, RNA-seq, and genetic approaches, we show that transcription of a gene encoding a PDE, cdgC, is activated by VpsR at high c-di-GMP concentrations, mediating this negative feedback on c-di-GMP levels. Further, although cells lacking cdgC exhibit enhanced biofilm formation, these mutants are outcompeted by wild type V. cholerae in colonization assays that reward a combination of attachment, dispersal, and motility behaviors. These results underscore the importance of negative feedback regulation of c-di-GMP to maintain appropriate homeostatic levels for efficient transitioning between biofilm formation and motility, both of which are necessary over the course of the V. cholerae infection cycle.

microbiology↗

bioRxiv2024

InterLabelGO+: Unraveling label correlations in protein function prediction

MotivationAccurate protein function prediction is crucial for understanding biological processes and advancing biomedical research. However, the rapid growth of protein sequences far outpaces the experimental characterization of their functions, necessitating the development of automated computational methods. ResultsWe present InterLabelGO+, a hybrid approach that integrates a deep learning-based method with an alignment-based method for improved protein function prediction. InterLabelGO+ incorporates a novel loss function that addresses label dependency and imbalance and further enhances performance through dynamic weighting of the alignment-based component. A preliminary version of InterLabelGO+ achieved a strong performance in the CAFA5 challenge, ranking 6th out of 1,625 participating teams. Comprehensive evaluations on large-scale protein function prediction tasks demonstrate InterLabelGO+s ability to accurately predict Gene Ontology terms across various functional categories and evaluation metrics. Availability and ImplementationThe source code and datasets for InterLabelGO+ are freely available on GitHub at https://github.com/QuanEvans/InterLabelGO. The software is implemented in Python and PyTorch, and is supported on Linux and macOS. Contactlydsf@umich.edu (LF) and zcx@umich.edu (CZ)

bioinformatics↗

bioRxiv2024

StarFunc: fusing template-based and deep learning approaches for accurate protein function prediction

Deep learning has significantly advanced the development of high-performance methods for protein function prediction. Nonetheless, even for state-of-the-art deep learning approaches, template information remains an indispensable component in most cases. While many function prediction methods use templates identified through sequence homology or protein-protein interactions, very few methods detect templates through structural similarity, even though protein structures are the basis of their functions. Here, we describe our development of StarFunc, a composite approach that integrates state-of-the-art deep learning models seamlessly with template information from sequence homology, protein-protein interaction partners, proteins with similar structures, and protein domain families. Large-scale benchmarking and blind testing in the 5th Critical Assessment of Function Annotation (CAFA5) consistently demonstrate StarFuncs advantage when compared to both state-of-the-art deep learning methods and conventional template-based predictors.

bioinformatics↗

bioRxiv2024

Nucleoid-associated proteins shape the global protein occupancy and transcriptional landscape of a clinical isolate of Vibrio cholerae

Vibrio cholerae, the causative agent of the diarrheal disease cholera, poses an ongoing health threat due to its wide repertoire of horizontally acquired elements (HAEs) and virulence factors. New clinical isolates of the bacterium with improved fitness abilities, often associated with HAEs, frequently emerge. The appropriate control and expression of such genetic elements is critical for the bacteria to thrive in the different environmental niches it occupies. H-NS, the histone-like nucleoid structuring protein, is the best studied xenogeneic silencer of HAEs in gamma-proteobacteria. Although H-NS and other highly abundant nucleoid-associated proteins (NAPs) have been shown to play important roles in regulating HAEs and virulence in model bacteria, we still lack a comprehensive understanding of how different NAPs modulate transcription in V. cholerae. By obtaining genome-wide measurements of protein occupancy and active transcription in a clinical isolate of V. cholerae, harboring recently discovered HAEs encoding for phage defense systems, we show that a lack of H-NS causes a robust increase in the expression of genes found in many HAEs. We further found that TsrA, a protein with partial homology to H-NS, regulates virulence genes primarily through modulation of H-NS activity. We also identified a few sites that are affected by TsrA independently of H-NS, suggesting TsrA may act with diverse regulatory mechanisms. Our results demonstrate how the combinatorial activity of NAPs is employed by a clinical isolate of an important pathogen to regulate recently discovered HAEs. ImportanceNew strains of the bacterial pathogen Vibrio cholerae, bearing novel horizontally acquired elements (HAEs), frequently emerge. HAEs provide beneficial traits to the bacterium, such as antibiotic resistance and defense against invading bacteriophages. Xenogeneic silencers are proteins that help bacteria harness new HAEs and silence those HAEs until they are needed. H-NS is the best-studied xenogeneic silencer; it is one of the nucleoid-associated proteins (NAPs) in gamma-proteobacteria and is responsible for the proper regulation of HAEs within the bacterial transcriptional network. We studied the effects of H-NS and other NAPs on the HAEs of a clinical isolate of V. cholerae. Importantly, we found that H-NS partners with a small and poorly characterized protein, TsrA, to help domesticate new HAEs involved in bacterial survival and in causing disease. Proper understanding of the regulatory state in emerging isolates of V. cholerae will provide improved therapies against new isolates of the pathogen.

microbiology↗